DISEASE SPECIFIC ATLASES

Disease-specific atlases are designed to reflect the unique anatomy and physiology of a particular clinical subpopulation. Based on well-characterized patient groups, these atlases contain thousands of structure models, as well as composite maps, average templates, and visualizations of structural variability, asymmetry and group-specific differences. They act as a quantitative framework that correlates the structural, metabolic, molecular and histologic hallmarks of the disease. Additional algorithms are described that use information stored in the atlas to recognize anomalies and label structures in new patients. Because they retain information on group anatomical variability, disease-specific atlases are a type of probabilistic atlas specialized to represent a particular clinical group. The resulting atlases can identify patterns of altered structure or function, and can guide algorithms for knowledge-based image analysis, automated image labeling, tissue classification, and functional image analysis.

• Genetic Atlases
  Inclusion of genetic data in an atlas makes it possible to go beyond describing a disease to investigating its causes. Novel mathematics can be used to mine imaging data, and to identify genetic sources of variation. This allows the direct mapping of genetic influences on brain structure, and lets us quantify heritability for different features of the brain. Familial, twin and genetic linkage studies have recently begun to expand the atlas concept to tie together genetic and imaging studies of disease. Atlases that contain genetic brain maps, and a means to analyze them, can help screen relatives for inherited disease. They also offer a framework to mine large imaging databases for risk genes and quantitative trait loci, as well as genetic and environmental triggers of disease.